Overview

Brought to you by YData

Dataset statistics

Number of variables17
Number of observations1048532
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.4 MiB
Average record size in memory976.5 B

Variable types

Categorical6
Text9
DateTime1
Numeric1

Alerts

Application Number has unique values Unique

Reproduction

Analysis started2025-03-26 05:52:37.040183
Analysis finished2025-03-26 05:53:17.642068
Duration40.6 seconds
Software versionydata-profiling vv4.15.1
Download configurationconfig.json

Variables

Gender
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.9 MiB
Male
576993 
Female
461118 
Other
 
10421

Length

Max length6
Median length4
Mean length4.8894884
Min length4

Characters and Unicode

Total characters5126785
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowFemale
3rd rowMale
4th rowFemale
5th rowMale

Common Values

ValueCountFrequency (%)
Male 576993
55.0%
Female 461118
44.0%
Other 10421
 
1.0%

Length

2025-03-26T11:23:17.735861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T11:23:17.806202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
male 576993
55.0%
female 461118
44.0%
other 10421
 
1.0%

Most occurring characters

ValueCountFrequency (%)
e 1509650
29.4%
a 1038111
20.2%
l 1038111
20.2%
M 576993
 
11.3%
F 461118
 
9.0%
m 461118
 
9.0%
O 10421
 
0.2%
t 10421
 
0.2%
h 10421
 
0.2%
r 10421
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5126785
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1509650
29.4%
a 1038111
20.2%
l 1038111
20.2%
M 576993
 
11.3%
F 461118
 
9.0%
m 461118
 
9.0%
O 10421
 
0.2%
t 10421
 
0.2%
h 10421
 
0.2%
r 10421
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5126785
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1509650
29.4%
a 1038111
20.2%
l 1038111
20.2%
M 576993
 
11.3%
F 461118
 
9.0%
m 461118
 
9.0%
O 10421
 
0.2%
t 10421
 
0.2%
h 10421
 
0.2%
r 10421
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5126785
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1509650
29.4%
a 1038111
20.2%
l 1038111
20.2%
M 576993
 
11.3%
F 461118
 
9.0%
m 461118
 
9.0%
O 10421
 
0.2%
t 10421
 
0.2%
h 10421
 
0.2%
r 10421
 
0.2%

State/UT
Categorical

Distinct36
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.9 MiB
Gujarat
195852 
Maharashtra
108792 
Uttar Pradesh
99944 
Rajasthan
85282 
Karnataka
59982 
Other values (31)
498680 

Length

Max length40
Median length17
Mean length9.8896018
Min length3

Characters and Unicode

Total characters10369564
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTamil Nadu
2nd rowTelangana
3rd rowGujarat
4th rowUttar Pradesh
5th rowManipur

Common Values

ValueCountFrequency (%)
Gujarat 195852
18.7%
Maharashtra 108792
 
10.4%
Uttar Pradesh 99944
 
9.5%
Rajasthan 85282
 
8.1%
Karnataka 59982
 
5.7%
Telangana 59628
 
5.7%
Andhra Pradesh 55646
 
5.3%
Madhya Pradesh 40213
 
3.8%
Tamil Nadu 34890
 
3.3%
Haryana 20763
 
2.0%
Other values (26) 287540
27.4%

Length

2025-03-26T11:23:17.903597image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pradesh 212061
15.1%
gujarat 195852
14.0%
maharashtra 108792
 
7.8%
uttar 99944
 
7.1%
rajasthan 85282
 
6.1%
karnataka 59982
 
4.3%
telangana 59628
 
4.2%
andhra 55646
 
4.0%
and 41202
 
2.9%
madhya 40213
 
2.9%
Other values (37) 445100
31.7%

Most occurring characters

ValueCountFrequency (%)
a 2614376
25.2%
r 1047251
10.1%
h 822842
 
7.9%
t 723997
 
7.0%
n 507162
 
4.9%
s 501336
 
4.8%
d 498843
 
4.8%
e 362436
 
3.5%
355170
 
3.4%
u 319262
 
3.1%
Other values (33) 2616889
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10369564
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2614376
25.2%
r 1047251
10.1%
h 822842
 
7.9%
t 723997
 
7.0%
n 507162
 
4.9%
s 501336
 
4.8%
d 498843
 
4.8%
e 362436
 
3.5%
355170
 
3.4%
u 319262
 
3.1%
Other values (33) 2616889
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10369564
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2614376
25.2%
r 1047251
10.1%
h 822842
 
7.9%
t 723997
 
7.0%
n 507162
 
4.9%
s 501336
 
4.8%
d 498843
 
4.8%
e 362436
 
3.5%
355170
 
3.4%
u 319262
 
3.1%
Other values (33) 2616889
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10369564
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2614376
25.2%
r 1047251
10.1%
h 822842
 
7.9%
t 723997
 
7.0%
n 507162
 
4.9%
s 501336
 
4.8%
d 498843
 
4.8%
e 362436
 
3.5%
355170
 
3.4%
u 319262
 
3.1%
Other values (33) 2616889
25.2%
Distinct733
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-26T11:23:18.124172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.4266508
Min length3

Characters and Unicode

Total characters8835613
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThanjavur
2nd rowWarangal Urban
3rd rowNarmada
4th rowJaunpur
5th rowKangpokpi
ValueCountFrequency (%)
north 19258
 
1.6%
south 17963
 
1.5%
west 11272
 
0.9%
east 10887
 
0.9%
goa 10521
 
0.9%
sikkim 10504
 
0.9%
mumbai 10336
 
0.9%
chandigarh 10205
 
0.8%
kachchh 10005
 
0.8%
junagadh 9824
 
0.8%
Other values (736) 1094690
90.1%
2025-03-26T11:23:18.439877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1788322
20.2%
r 728023
 
8.2%
h 559111
 
6.3%
i 527777
 
6.0%
n 514919
 
5.8%
u 425621
 
4.8%
d 339277
 
3.8%
o 323347
 
3.7%
l 308370
 
3.5%
g 268218
 
3.0%
Other values (44) 3052628
34.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8835613
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1788322
20.2%
r 728023
 
8.2%
h 559111
 
6.3%
i 527777
 
6.0%
n 514919
 
5.8%
u 425621
 
4.8%
d 339277
 
3.8%
o 323347
 
3.7%
l 308370
 
3.5%
g 268218
 
3.0%
Other values (44) 3052628
34.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8835613
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1788322
20.2%
r 728023
 
8.2%
h 559111
 
6.3%
i 527777
 
6.0%
n 514919
 
5.8%
u 425621
 
4.8%
d 339277
 
3.8%
o 323347
 
3.7%
l 308370
 
3.5%
g 268218
 
3.0%
Other values (44) 3052628
34.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8835613
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1788322
20.2%
r 728023
 
8.2%
h 559111
 
6.3%
i 527777
 
6.0%
n 514919
 
5.8%
u 425621
 
4.8%
d 339277
 
3.8%
o 323347
 
3.7%
l 308370
 
3.5%
g 268218
 
3.0%
Other values (44) 3052628
34.5%

RWA/Residential
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 MiB
Residential
851827 
RWA
196705 

Length

Max length11
Median length11
Mean length9.499197
Min length3

Characters and Unicode

Total characters9960212
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResidential
2nd rowResidential
3rd rowResidential
4th rowRWA
5th rowResidential

Common Values

ValueCountFrequency (%)
Residential 851827
81.2%
RWA 196705
 
18.8%

Length

2025-03-26T11:23:18.543490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T11:23:18.614348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
residential 851827
81.2%
rwa 196705
 
18.8%

Most occurring characters

ValueCountFrequency (%)
e 1703654
17.1%
i 1703654
17.1%
R 1048532
10.5%
s 851827
8.6%
d 851827
8.6%
n 851827
8.6%
t 851827
8.6%
a 851827
8.6%
l 851827
8.6%
W 196705
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9960212
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1703654
17.1%
i 1703654
17.1%
R 1048532
10.5%
s 851827
8.6%
d 851827
8.6%
n 851827
8.6%
t 851827
8.6%
a 851827
8.6%
l 851827
8.6%
W 196705
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9960212
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1703654
17.1%
i 1703654
17.1%
R 1048532
10.5%
s 851827
8.6%
d 851827
8.6%
n 851827
8.6%
t 851827
8.6%
a 851827
8.6%
l 851827
8.6%
W 196705
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9960212
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1703654
17.1%
i 1703654
17.1%
R 1048532
10.5%
s 851827
8.6%
d 851827
8.6%
n 851827
8.6%
t 851827
8.6%
a 851827
8.6%
l 851827
8.6%
W 196705
 
2.0%
Distinct56
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size96.6 MiB
2025-03-26T11:23:18.789702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length69
Median length58
Mean length47.611519
Min length10

Characters and Unicode

Total characters49922201
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)
2nd rowSouthern Power Distribution Company of Telangana Limited (TSSPDCL)
3rd rowTorrent Power Limited, Ahmedabad
4th rowLucknow Electricity Supply Administration (LESA), Lucknow City
5th rowManipur State Power Distribution Company Limited (MSPDCL)
ValueCountFrequency (%)
limited 701743
 
11.0%
company 444008
 
6.9%
power 323293
 
5.1%
corporation 250586
 
3.9%
distribution 222206
 
3.5%
electricity 196077
 
3.1%
of 184389
 
2.9%
vidyut 170515
 
2.7%
vij 151596
 
2.4%
gujarat 151596
 
2.4%
Other values (125) 3598891
56.3%
2025-03-26T11:23:19.137874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5346368
 
10.7%
i 4256706
 
8.5%
a 3958154
 
7.9%
t 3302049
 
6.6%
r 3054343
 
6.1%
o 2641438
 
5.3%
n 2276490
 
4.6%
e 2266660
 
4.5%
d 1819164
 
3.6%
m 1716538
 
3.4%
Other values (41) 19284291
38.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49922201
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5346368
 
10.7%
i 4256706
 
8.5%
a 3958154
 
7.9%
t 3302049
 
6.6%
r 3054343
 
6.1%
o 2641438
 
5.3%
n 2276490
 
4.6%
e 2266660
 
4.5%
d 1819164
 
3.6%
m 1716538
 
3.4%
Other values (41) 19284291
38.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49922201
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5346368
 
10.7%
i 4256706
 
8.5%
a 3958154
 
7.9%
t 3302049
 
6.6%
r 3054343
 
6.1%
o 2641438
 
5.3%
n 2276490
 
4.6%
e 2266660
 
4.5%
d 1819164
 
3.6%
m 1716538
 
3.4%
Other values (41) 19284291
38.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49922201
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5346368
 
10.7%
i 4256706
 
8.5%
a 3958154
 
7.9%
t 3302049
 
6.6%
r 3054343
 
6.1%
o 2641438
 
5.3%
n 2276490
 
4.6%
e 2266660
 
4.5%
d 1819164
 
3.6%
m 1716538
 
3.4%
Other values (41) 19284291
38.6%
Distinct366
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.0 MiB
Minimum2024-01-01 00:00:00
Maximum2024-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-26T11:23:19.249349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-26T11:23:19.380363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
Rejected
737467 
Accepted
311065 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8388256
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAccepted
2nd rowRejected
3rd rowAccepted
4th rowRejected
5th rowAccepted

Common Values

ValueCountFrequency (%)
Rejected 737467
70.3%
Accepted 311065
29.7%

Length

2025-03-26T11:23:19.482802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T11:23:19.545846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
rejected 737467
70.3%
accepted 311065
29.7%

Most occurring characters

ValueCountFrequency (%)
e 2834531
33.8%
c 1359597
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 737467
 
8.8%
R 737467
 
8.8%
A 311065
 
3.7%
p 311065
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2834531
33.8%
c 1359597
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 737467
 
8.8%
R 737467
 
8.8%
A 311065
 
3.7%
p 311065
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2834531
33.8%
c 1359597
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 737467
 
8.8%
R 737467
 
8.8%
A 311065
 
3.7%
p 311065
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2834531
33.8%
c 1359597
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 737467
 
8.8%
R 737467
 
8.8%
A 311065
 
3.7%
p 311065
 
3.7%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
3 - 4 KW
735047 
4 - 5 KW
153554 
5 - 6 KW
76752 
2 - 3 KW
 
58570
Above 6 KW
 
20730

Length

Max length10
Median length8
Mean length8.039541
Min length8

Characters and Unicode

Total characters8429716
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3 - 4 KW
2nd row4 - 5 KW
3rd row3 - 4 KW
4th row4 - 5 KW
5th row3 - 4 KW

Common Values

ValueCountFrequency (%)
3 - 4 KW 735047
70.1%
4 - 5 KW 153554
 
14.6%
5 - 6 KW 76752
 
7.3%
2 - 3 KW 58570
 
5.6%
Above 6 KW 20730
 
2.0%
1 - 2 KW 3879
 
0.4%

Length

2025-03-26T11:23:19.622440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-26T11:23:19.711741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
kw 1048532
25.1%
1027802
24.6%
4 888601
21.3%
3 793617
19.0%
5 230306
 
5.5%
6 97482
 
2.3%
2 62449
 
1.5%
above 20730
 
0.5%
1 3879
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3124866
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027802
 
12.2%
4 888601
 
10.5%
3 793617
 
9.4%
5 230306
 
2.7%
6 97482
 
1.2%
2 62449
 
0.7%
A 20730
 
0.2%
Other values (5) 86799
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8429716
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3124866
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027802
 
12.2%
4 888601
 
10.5%
3 793617
 
9.4%
5 230306
 
2.7%
6 97482
 
1.2%
2 62449
 
0.7%
A 20730
 
0.2%
Other values (5) 86799
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8429716
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3124866
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027802
 
12.2%
4 888601
 
10.5%
3 793617
 
9.4%
5 230306
 
2.7%
6 97482
 
1.2%
2 62449
 
0.7%
A 20730
 
0.2%
Other values (5) 86799
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8429716
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3124866
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027802
 
12.2%
4 888601
 
10.5%
3 793617
 
9.4%
5 230306
 
2.7%
6 97482
 
1.2%
2 62449
 
0.7%
A 20730
 
0.2%
Other values (5) 86799
 
1.0%

Application Number
Real number (ℝ)

Unique 

Distinct1048532
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54983020
Minimum10000035
Maximum99999955
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 MiB
2025-03-26T11:23:19.834389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10000035
5-th percentile14526545
Q132529609
median54931118
Q377464184
95-th percentile95496792
Maximum99999955
Range89999920
Interquartile range (IQR)44934575

Descriptive statistics

Standard deviation25960777
Coefficient of variation (CV)0.47215989
Kurtosis-1.1978051
Mean54983020
Median Absolute Deviation (MAD)22471296
Skewness0.0018595998
Sum5.7651456 × 1013
Variance6.7396194 × 1014
MonotonicityNot monotonic
2025-03-26T11:23:19.950656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61641528 1
 
< 0.1%
87593586 1
 
< 0.1%
40957248 1
 
< 0.1%
20779751 1
 
< 0.1%
50672476 1
 
< 0.1%
81758085 1
 
< 0.1%
65708892 1
 
< 0.1%
27567722 1
 
< 0.1%
52347968 1
 
< 0.1%
25149612 1
 
< 0.1%
Other values (1048522) 1048522
> 99.9%
ValueCountFrequency (%)
10000035 1
< 0.1%
10000104 1
< 0.1%
10000186 1
< 0.1%
10000247 1
< 0.1%
10000307 1
< 0.1%
10000394 1
< 0.1%
10000474 1
< 0.1%
10000564 1
< 0.1%
10000570 1
< 0.1%
10000690 1
< 0.1%
ValueCountFrequency (%)
99999955 1
< 0.1%
99999799 1
< 0.1%
99999572 1
< 0.1%
99999405 1
< 0.1%
99999240 1
< 0.1%
99999141 1
< 0.1%
99999128 1
< 0.1%
99999038 1
< 0.1%
99998976 1
< 0.1%
99998951 1
< 0.1%
Distinct365
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
2025-03-26T11:23:20.187886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5786738
Min length7

Characters and Unicode

Total characters8995014
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-09-09
2nd rowDeclined
3rd row2024-10-16
4th rowDeclined
5th row2024-04-10
ValueCountFrequency (%)
declined 737467
70.3%
pending 5124
 
0.5%
2024-06-25 968
 
0.1%
2024-11-26 967
 
0.1%
2024-02-15 950
 
0.1%
2024-06-24 935
 
0.1%
2024-11-22 930
 
0.1%
2024-02-12 930
 
0.1%
2024-02-16 924
 
0.1%
2024-02-27 922
 
0.1%
Other values (355) 298415
28.5%
2025-03-26T11:23:20.642915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1480058
16.5%
2 795745
8.8%
n 747715
8.3%
d 742591
8.3%
i 742591
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 675765
7.5%
- 611882
6.8%
Other values (10) 986266
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8995014
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1480058
16.5%
2 795745
8.8%
n 747715
8.3%
d 742591
8.3%
i 742591
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 675765
7.5%
- 611882
6.8%
Other values (10) 986266
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8995014
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1480058
16.5%
2 795745
8.8%
n 747715
8.3%
d 742591
8.3%
i 742591
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 675765
7.5%
- 611882
6.8%
Other values (10) 986266
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8995014
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1480058
16.5%
2 795745
8.8%
n 747715
8.3%
d 742591
8.3%
i 742591
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 675765
7.5%
- 611882
6.8%
Other values (10) 986266
11.0%
Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 MiB
SkyPower Solar
83513 
BrightSun Power
78899 
GreenSpark Solar
74358 
RadiantSun Energy
74342 
SunWave Energy
70100 
Other values (15)
667320 

Length

Max length27
Median length23
Mean length18.874603
Min length13

Characters and Unicode

Total characters19790625
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSunVolt Power
2nd rowSunWave Energy
3rd rowSunWave Energy
4th rowSunRise Renewable Solutions
5th rowSunVolt Power

Common Values

ValueCountFrequency (%)
SkyPower Solar 83513
 
8.0%
BrightSun Power 78899
 
7.5%
GreenSpark Solar 74358
 
7.1%
RadiantSun Energy 74342
 
7.1%
SunWave Energy 70100
 
6.7%
SunTech Solar Solutions 65703
 
6.3%
SunRise Renewable Solutions 60987
 
5.8%
SolarPeak Innovations 56512
 
5.4%
SolarHarvest Energy 56501
 
5.4%
InfiniteLight Solar 52371
 
5.0%
Other values (10) 375246
35.8%

Length

2025-03-26T11:23:20.739753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
solar 341267
 
14.9%
energy 231248
 
10.1%
solutions 156995
 
6.8%
power 118048
 
5.1%
systems 104753
 
4.6%
technologies 96231
 
4.2%
skypower 83513
 
3.6%
brightsun 78899
 
3.4%
enterprises 78737
 
3.4%
greenspark 74358
 
3.2%
Other values (19) 929261
40.5%

Most occurring characters

ValueCountFrequency (%)
e 2009557
 
10.2%
n 1737801
 
8.8%
r 1674202
 
8.5%
o 1549936
 
7.8%
S 1490062
 
7.5%
1244778
 
6.3%
a 1196011
 
6.0%
l 1004237
 
5.1%
t 842717
 
4.3%
s 838219
 
4.2%
Other values (26) 6203105
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19790625
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2009557
 
10.2%
n 1737801
 
8.8%
r 1674202
 
8.5%
o 1549936
 
7.8%
S 1490062
 
7.5%
1244778
 
6.3%
a 1196011
 
6.0%
l 1004237
 
5.1%
t 842717
 
4.3%
s 838219
 
4.2%
Other values (26) 6203105
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19790625
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2009557
 
10.2%
n 1737801
 
8.8%
r 1674202
 
8.5%
o 1549936
 
7.8%
S 1490062
 
7.5%
1244778
 
6.3%
a 1196011
 
6.0%
l 1004237
 
5.1%
t 842717
 
4.3%
s 838219
 
4.2%
Other values (26) 6203105
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19790625
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2009557
 
10.2%
n 1737801
 
8.8%
r 1674202
 
8.5%
o 1549936
 
7.8%
S 1490062
 
7.5%
1244778
 
6.3%
a 1196011
 
6.0%
l 1004237
 
5.1%
t 842717
 
4.3%
s 838219
 
4.2%
Other values (26) 6203105
31.3%
Distinct360
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
2025-03-26T11:23:20.969666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5605799
Min length7

Characters and Unicode

Total characters8976042
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-09-16
2nd rowDeclined
3rd row2024-10-29
4th rowDeclined
5th row2024-04-19
ValueCountFrequency (%)
declined 737467
70.3%
pending 11448
 
1.1%
2024-02-26 949
 
0.1%
2024-02-20 949
 
0.1%
2024-02-17 940
 
0.1%
2024-02-22 939
 
0.1%
2024-03-10 929
 
0.1%
2024-03-16 927
 
0.1%
2024-02-15 924
 
0.1%
2024-07-06 924
 
0.1%
Other values (350) 292136
 
27.9%
2025-03-26T11:23:21.317627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1486382
16.6%
2 782029
8.7%
n 760363
8.5%
d 748915
8.3%
i 748915
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 660891
7.4%
- 599234
6.7%
Other values (10) 976912
10.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8976042
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1486382
16.6%
2 782029
8.7%
n 760363
8.5%
d 748915
8.3%
i 748915
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 660891
7.4%
- 599234
6.7%
Other values (10) 976912
10.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8976042
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1486382
16.6%
2 782029
8.7%
n 760363
8.5%
d 748915
8.3%
i 748915
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 660891
7.4%
- 599234
6.7%
Other values (10) 976912
10.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8976042
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1486382
16.6%
2 782029
8.7%
n 760363
8.5%
d 748915
8.3%
i 748915
8.3%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 660891
7.4%
- 599234
6.7%
Other values (10) 976912
10.9%
Distinct358
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
2025-03-26T11:23:21.541037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5529407
Min length7

Characters and Unicode

Total characters8968032
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-09-20
2nd rowDeclined
3rd row2024-11-02
4th rowDeclined
5th row2024-04-22
ValueCountFrequency (%)
declined 737467
70.3%
pending 14118
 
1.3%
2024-02-23 967
 
0.1%
2024-03-11 951
 
0.1%
2024-09-07 948
 
0.1%
2024-12-19 935
 
0.1%
2024-09-29 931
 
0.1%
2024-03-07 930
 
0.1%
2024-02-26 930
 
0.1%
2024-03-13 928
 
0.1%
Other values (348) 289427
 
27.6%
2025-03-26T11:23:21.889227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1489052
16.6%
2 776028
8.7%
n 765703
8.5%
d 751585
8.4%
i 751585
8.4%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 654880
7.3%
- 593894
 
6.6%
Other values (10) 972904
10.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8968032
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1489052
16.6%
2 776028
8.7%
n 765703
8.5%
d 751585
8.4%
i 751585
8.4%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 654880
7.3%
- 593894
 
6.6%
Other values (10) 972904
10.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8968032
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1489052
16.6%
2 776028
8.7%
n 765703
8.5%
d 751585
8.4%
i 751585
8.4%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 654880
7.3%
- 593894
 
6.6%
Other values (10) 972904
10.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8968032
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1489052
16.6%
2 776028
8.7%
n 765703
8.5%
d 751585
8.4%
i 751585
8.4%
l 737467
8.2%
D 737467
8.2%
c 737467
8.2%
0 654880
7.3%
- 593894
 
6.6%
Other values (10) 972904
10.8%
Distinct348
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-26T11:23:22.112167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4611037
Min length7

Characters and Unicode

Total characters8871738
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-10-13
2nd rowDeclined
3rd row2024-11-28
4th rowDeclined
5th row2024-05-27
ValueCountFrequency (%)
declined 737467
70.3%
pending 46216
 
4.4%
2024-03-25 961
 
0.1%
2024-03-12 947
 
0.1%
2024-10-15 938
 
0.1%
2024-07-18 929
 
0.1%
2024-05-19 925
 
0.1%
2024-05-23 914
 
0.1%
2024-03-20 910
 
0.1%
2024-03-21 908
 
0.1%
Other values (338) 257417
 
24.6%
2025-03-26T11:23:22.482020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 675199
7.6%
0 595479
 
6.7%
- 529698
 
6.0%
Other values (10) 940546
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8871738
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 675199
7.6%
0 595479
 
6.7%
- 529698
 
6.0%
Other values (10) 940546
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8871738
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 675199
7.6%
0 595479
 
6.7%
- 529698
 
6.0%
Other values (10) 940546
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8871738
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 675199
7.6%
0 595479
 
6.7%
- 529698
 
6.0%
Other values (10) 940546
10.6%
Distinct355
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-26T11:23:22.693980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4611037
Min length7

Characters and Unicode

Total characters8871738
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2024-10-18
2nd rowDeclined
3rd row2024-12-06
4th rowDeclined
5th row2024-06-05
ValueCountFrequency (%)
declined 737467
70.3%
pending 46216
 
4.4%
2024-04-02 939
 
0.1%
2024-08-03 933
 
0.1%
2024-03-30 925
 
0.1%
2024-03-22 920
 
0.1%
2024-03-25 919
 
0.1%
2024-03-27 918
 
0.1%
2024-07-26 911
 
0.1%
2024-03-17 908
 
0.1%
Other values (345) 257476
 
24.6%
2025-03-26T11:23:23.033921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 672880
7.6%
0 591326
 
6.7%
- 529698
 
6.0%
Other values (10) 947018
10.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8871738
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 672880
7.6%
0 591326
 
6.7%
- 529698
 
6.0%
Other values (10) 947018
10.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8871738
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 672880
7.6%
0 591326
 
6.7%
- 529698
 
6.0%
Other values (10) 947018
10.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8871738
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1521150
17.1%
n 829899
9.4%
i 783683
8.8%
d 783683
8.8%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 672880
7.6%
0 591326
 
6.7%
- 529698
 
6.0%
Other values (10) 947018
10.7%
Distinct365
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-26T11:23:23.250664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4545317
Min length7

Characters and Unicode

Total characters8864847
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row2024-10-25
2nd rowDeclined
3rd row2024-12-14
4th rowDeclined
5th row2024-06-17
ValueCountFrequency (%)
declined 737467
70.3%
pending 48513
 
4.6%
2024-04-01 938
 
0.1%
2024-04-11 934
 
0.1%
2024-04-19 932
 
0.1%
2024-04-14 925
 
0.1%
2024-04-18 924
 
0.1%
2024-08-04 922
 
0.1%
2024-07-11 919
 
0.1%
2024-08-14 916
 
0.1%
Other values (355) 255142
 
24.3%
2025-03-26T11:23:23.592141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1523447
17.2%
n 834493
9.4%
i 785980
8.9%
d 785980
8.9%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 662728
7.5%
0 582372
 
6.6%
- 525104
 
5.9%
Other values (10) 952342
10.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8864847
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1523447
17.2%
n 834493
9.4%
i 785980
8.9%
d 785980
8.9%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 662728
7.5%
0 582372
 
6.6%
- 525104
 
5.9%
Other values (10) 952342
10.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8864847
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1523447
17.2%
n 834493
9.4%
i 785980
8.9%
d 785980
8.9%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 662728
7.5%
0 582372
 
6.6%
- 525104
 
5.9%
Other values (10) 952342
10.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8864847
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1523447
17.2%
n 834493
9.4%
i 785980
8.9%
d 785980
8.9%
l 737467
8.3%
c 737467
8.3%
D 737467
8.3%
2 662728
7.5%
0 582372
 
6.6%
- 525104
 
5.9%
Other values (10) 952342
10.7%
Distinct302
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.2 MiB
2025-03-26T11:23:23.813651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1800737
Min length7

Characters and Unicode

Total characters8577069
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowPending
2nd rowDeclined
3rd rowPending
4th rowDeclined
5th row2024-08-20
ValueCountFrequency (%)
declined 737467
70.3%
pending 144439
 
13.8%
2024-08-01 884
 
0.1%
2024-08-14 884
 
0.1%
2024-08-18 874
 
0.1%
2024-08-28 865
 
0.1%
2024-07-19 852
 
0.1%
2024-07-17 852
 
0.1%
2024-08-29 847
 
0.1%
2024-08-30 842
 
0.1%
Other values (292) 159726
 
15.2%
2025-03-26T11:23:24.125640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1619373
18.9%
n 1026345
12.0%
i 881906
10.3%
d 881906
10.3%
l 737467
8.6%
c 737467
8.6%
D 737467
8.6%
2 417752
 
4.9%
0 367630
 
4.3%
- 333252
 
3.9%
Other values (10) 836504
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8577069
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1619373
18.9%
n 1026345
12.0%
i 881906
10.3%
d 881906
10.3%
l 737467
8.6%
c 737467
8.6%
D 737467
8.6%
2 417752
 
4.9%
0 367630
 
4.3%
- 333252
 
3.9%
Other values (10) 836504
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8577069
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1619373
18.9%
n 1026345
12.0%
i 881906
10.3%
d 881906
10.3%
l 737467
8.6%
c 737467
8.6%
D 737467
8.6%
2 417752
 
4.9%
0 367630
 
4.3%
- 333252
 
3.9%
Other values (10) 836504
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8577069
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1619373
18.9%
n 1026345
12.0%
i 881906
10.3%
d 881906
10.3%
l 737467
8.6%
c 737467
8.6%
D 737467
8.6%
2 417752
 
4.9%
0 367630
 
4.3%
- 333252
 
3.9%
Other values (10) 836504
9.8%

Interactions

2025-03-26T11:23:12.916852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-26T11:23:24.206591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Acceptance StatusApplication NumberGenderProduction Capacity (KW)RWA/ResidentialState/UTVendor Organization
Acceptance Status1.0000.0000.0000.0000.0010.1170.004
Application Number0.0001.0000.0020.0000.0000.0010.000
Gender0.0000.0021.0000.0000.0000.0000.003
Production Capacity (KW)0.0000.0000.0001.0000.0000.0020.000
RWA/Residential0.0010.0000.0000.0001.0000.0520.000
State/UT0.1170.0010.0000.0020.0521.0000.002
Vendor Organization0.0040.0000.0030.0000.0000.0021.000

Missing values

2025-03-26T11:23:13.671544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-26T11:23:15.178090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

GenderState/UTDistrictRWA/ResidentialDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
0FemaleTamil NaduThanjavurResidentialTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)2024-09-03Accepted3 - 4 KW875935862024-09-09SunVolt Power2024-09-162024-09-202024-10-132024-10-182024-10-25Pending
1FemaleTelanganaWarangal UrbanResidentialSouthern Power Distribution Company of Telangana Limited (TSSPDCL)2024-02-13Rejected4 - 5 KW40957248DeclinedSunWave EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
2MaleGujaratNarmadaResidentialTorrent Power Limited, Ahmedabad2024-10-13Accepted3 - 4 KW207797512024-10-16SunWave Energy2024-10-292024-11-022024-11-282024-12-062024-12-14Pending
3FemaleUttar PradeshJaunpurRWALucknow Electricity Supply Administration (LESA), Lucknow City2024-09-30Rejected4 - 5 KW42572396DeclinedSunRise Renewable SolutionsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
4MaleManipurKangpokpiResidentialManipur State Power Distribution Company Limited (MSPDCL)2024-04-01Accepted3 - 4 KW781151142024-04-10SunVolt Power2024-04-192024-04-222024-05-272024-06-052024-06-172024-08-20
5MaleKarnatakaKodaguResidentialGulbarga Electricity Supply Company Limited (GESCOM)2024-01-03Rejected3 - 4 KW13049505DeclinedSunVolt PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
6FemaleKarnatakaTumakuruRWAHubli Electricity Supply Company Limited (HESCOM)2024-10-20Accepted4 - 5 KW831876962024-10-27SunTech Solar Solutions2024-11-042024-11-062024-11-182024-11-252024-12-14Pending
7FemaleUttar PradeshFarrukhabadResidentialUttar Pradesh Power Corporation Limited (UPPCL)2024-12-18Accepted3 - 4 KW375400892024-12-26SkyPower SolarPendingPendingPendingPendingPendingPending
8FemaleUttar PradeshFirozabadResidentialMadhyanchal Vidyut Vitaran Nigam Limited (MVVNL), Lucknow Zone2024-01-29Rejected3 - 4 KW73041938DeclinedSunVolt PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
9MaleGujaratSurendranagarResidentialMadhya Gujarat Vij Company Limited (MGVCL), Vadodara2024-11-17Rejected3 - 4 KW86971499DeclinedSunWave EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
GenderState/UTDistrictRWA/ResidentialDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
1048522FemaleAndhra PradeshNelloreRWAAndhra Pradesh Central Power Distribution Company Limited2024-04-21Rejected3 - 4 KW31968914DeclinedBrightSun PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048523MaleTelanganaMuluguResidentialNorthern Power Distribution Company of Telangana Limited (TSNPDCL)2024-10-15Rejected3 - 4 KW23170038DeclinedSunTech Solar SolutionsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048524FemaleGujaratNavsariResidentialPaschim Gujarat Vij Company Limited (PGVCL), Rajkot2024-11-21Rejected3 - 4 KW97417772DeclinedRadiantSun EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048525MaleNagalandKiphireResidentialPowerGrid Corporation of India2024-05-26Rejected3 - 4 KW88042913DeclinedSolarPeak InnovationsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048526MaleGujaratMahisagarResidentialTorrent Power Limited, Ahmedabad2024-03-01Rejected4 - 5 KW58307265DeclinedBrightSun PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048527MaleDelhiNorth West DelhiResidentialTata Power Delhi Distribution Limited (TPDDL), Delhi2024-03-16Accepted4 - 5 KW508998042024-03-25RadiantSun Energy2024-04-012024-04-032024-05-052024-05-142024-05-262024-07-10
1048528FemaleArunachal PradeshWest SiangRWAPowerGrid Corporation of India2024-09-18Rejected4 - 5 KW75628550DeclinedSolarPeak InnovationsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048529FemaleTamil NaduKarurResidentialTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)2024-12-31Rejected3 - 4 KW53734140DeclinedInfiniteLight SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048530MaleGujaratJamnagarResidentialMadhya Gujarat Vij Company Limited (MGVCL), Vadodara2024-08-13Rejected3 - 4 KW43528067DeclinedEcoSolar EnterprisesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048531FemaleGujaratPanchmahalResidentialUttar Gujarat Vij Company Limited (UGVCL), Mehsana2024-11-28Rejected4 - 5 KW61641528DeclinedEcoPower SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined